Method and apparatus for laplace constrained touchscreen calibration

ABSTRACT

A computer readable medium has instructions to calibrate a touch system by detecting touch points on a touchscreen that are each associated with touchscreen coordinates in a touchscreen coordinate system. The instructions associated each of the touch points with known calibration targets, and each of the calibration targets has display coordinates in a display coordinate system that is associated with at least one of a display screen and an operating system. The instructions fit the display coordinates and the touchscreen coordinates non-linearly with respect to each other based on a generalized Laplace-constrained fit that is used to identify correction parameters used to map a user generated run-time touch point on the touchscreen to a display coordinate location on a display screen. The correction parameters represent non-linear corrections.

BACKGROUND OF THE INVENTION

This invention relates generally to touch display systems, and moreparticularly, to generating correction parameters used by algorithms tolocate run-time touches on touch display systems.

Touch displays and touch display systems are provided for an increasingnumber of applications. Point of sale (POS), for processing transactionswithin a department store, and point of information (POI), such as anelectronic directory are common. For example, applications includeairport passenger and baggage check-in, and kiosks located within astore that provide information about products and services. Furthermore,touch displays are increasingly used in handheld computing applicationssuch as for rental car check-in, package delivery services, andstockroom inventory management.

A touch display system has a display for visually presenting data to auser. A touchscreen is installed in front of the display. The userinteracts with the system by touching the touchscreen at locations oversoftware programmed buttons or icons in the displayed image or by movinga cursor via a moving touch. With the broad use of graphical userinterfaces (GUI) such as Microsoft Windows® that provide many smallbuttons, menu selections, and the like, it is increasingly important fortouchscreen measured locations to correspond with the desired cursorlocations in the display image. A number of calibration methods havebeen developed to properly map touchscreen coordinates to displaycoordinates. As used herein, “touchscreen coordinate system” refers tocoordinate locations detected as a result of a touch on the touchscreen,and “display coordinate system” refers to coordinate locations of pointson the display. In practice, touchscreen software communicatescoordinates to an operating system that has its own coordinate systemthat in turn is mapped to the coordinate locations of the points on thedisplay. Therefore, the term “display coordinate system” is generalizedherein to include operating system coordinate systems.

Linear and non-linear distortions may be present within the displays.Linear distortion may be one or more of horizontal and vertical offsetsas well as scale change or magnification. An example of lineardistortion is when equally spaced straight lines remain equally spacedstraight lines. With non-linear distortion, equally spaced straightlines are distorted such that lines are no longer straight nor equallyspaced, and may also have offset and scale distortions. For example,images on cathode ray tube (CRT) displays are subject to non-lineardistortions. Today, however, flat panel displays with minimal non-lineardistortion have largely replaced CRT displays and may include liquidcrystal displays (LCDs), plasma displays, electroluminescent displays,and organic light-emitting diode (OLED) displays, etc. The discussionherein assumes that the display coordinate system is free of non-lineardistortions.

Ideally, touchscreen hardware would be perfectly linear, generating xand y coordinates that differ from display coordinates by, at most,linear distortions. Even small touchscreen non-linear distortions may bea problem for GUI operation via a touch display system. Such non-lineardistortions of raw touchscreen coordinates may be due to touchscreenmanufacturing variations. Alternatively, the touchscreen may benon-linear by design as a consequence of other design objectives such asnarrow borders or reduced manufacturing cost. Due to thenon-linearities, there is demand for calibration methods to mapnon-linear touchscreen coordinates to linear display coordinates toassure that touches activate intended GUI icons.

There are many types of touchscreens that may be used in touch displaysystems. Touchscreen types include surface acoustic wave touchscreens,infrared touchscreens, capacitive touchscreens and 4-wire, 5-wire and9-wire resistive touchscreens. 5-wire touchscreens are a common choice.The basic principles of 5-wire touchscreen operation and forming of thetouchscreen substrate are described in the patent literature, such as inU.S. Pat. No. 6,593,916 (Elo Touchsystems, Inc., 2003).

In the construction of a typical 5-wire resistive touchscreen, a polymerfilm such as polyethylene terephthalate (PET) forms a coversheet that isplaced over a glass substrate with a narrow air gap in between. In theabsence of a touch, spacers prevent contact between the coversheet andglass substrate. The two surfaces facing the air gap are coated withtransparent conductive coatings such as indium tin oxide (ITO).Associated electronics and interconnections alternately apply X and Yvoltage gradients to the coating on the glass substrate. The coating onthe coversheet is connected to voltage sensing circuitry. A touch causesthe coversheet to deflect and contact the substrate thus making alocalized electrical connection between the conductive coatings. As aresult of this electrical contact, the local voltage on the glasssubstrate's coating is communicated to the coversheet coating which isconnected to voltage sensing circuitry. One voltage is measured when anX voltage gradient is applied to the glass substrate's coating andanother voltage is measured for a Y voltage gradient. These two voltagesare the raw touch (x,y) coordinate data. The voltage gradients are notperfect and may lead or contribute to non-linear and/or lineardistortions.

To form an exemplary 5-wire touchscreen substrate, a complex electrodegeometry composed of discrete electrodes is fabricated around theperimeter of the glass substrate. Such 5-wire touchscreen designs may bereferred to as discrete-electrode 5-wire resistive touchscreens orsimply discrete-electrode touchscreens. Discrete electrode touchscreenshave a discrete number of electrical connections to the resistivecoating that covers the touch area. Very close to the perimeter of thetouch area, the discreteness of these connections results in distortionsof the lines of constant voltage. In contrast, well away from theperimeter, the lines of constant voltage can be straight and equallyspaced and represent the ideal linear touchscreen. In some cases, inareas of a discrete-electrode touchscreen away from the perimeter, asmall, yet undesirable, amount of non-linearity may be experienced.

An alternative 5-wire touchscreen may be referred to as a picture-frametouchscreen and is discussed in U.S. Pat. No. 6,650,319 (EloTouchsystems, Inc., 2003). A resistive electrode in continuous contactwith the resistive coating surrounds the touch area much like a pictureframe surrounds a picture. The resistive picture-frame electrode resultsin curved lines of constant voltage or global bowing distortions.Picture-frame touchscreens are quite non-linear by design and depend onsoftware correction of non-linearity. The picture-frame touchscreendesign does provide a number of benefits including narrow borders aswell as the elimination of the perimeter distortions seen indiscrete-electrode touchscreen design.

Known methods exist for mapping touchscreen coordinates to displaycoordinates, such as 3-point calibration that may be used for linearmappings. More sophisticated calibration and mapping methods also existthat account for non-linear distortions within raw touchscreencoordinates.

U.S. Pat. No. 5,751,276 (Microsoft Corporation, 1998) proposes analternate linear calibration method in which redundant data is collectedand linear correction coefficients are determined from a least squaresfit. With the addition of two more calibration constants, linear sheardistortions and arbitrary rotations of the touchscreen coordinate systemwith respect to the display coordinate system can be corrected. However,it is still a linear correction scheme in which equally spaced straightlines remain equally spaced straight lines.

For many applications, 2-point or 3-point calibration is sufficient.This is often the case for applications that only involve user selectionof large icons or touch buttons. However, other applications are moredemanding, such as graphical user interfaces (GUI) that require precisecursor control to properly activate numerous small icons, buttons,scroll bars, etc. For such demanding applications, imperfections in thetouchscreen hardware may lead to unacceptable non-linear distortions ofthe touch system coordinates that cannot be corrected with the linear3-point calibration. Furthermore, if the touchscreen is non-linear bydesign, such as in a picture-frame touchscreen, the linear 3-pointcalibration method is insufficient.

Calibration methods involving more than three points that correct fornon-linear distortions are also known. For example Japanese patentapplication publication 2005-134992 (application JP 2003-367561) ofGunze proposes a 9-point calibration scheme to determine coefficients ofnon-linear corrections for picture-frame touchscreens. 25-pointcalibration procedures are also used.

Turning to a 25-point calibration, let (X₁, Y₁), (X₂, Y₂), . . . (X₂₅,Y₂₅) be the locations in the display coordinate system of 25 calibrationtargets imaged on the display device. The 25 calibration points may, forexample, be arranged in a 5 by 5 grid. As used herein, (X,Y) are displaysystem coordinates and (x,y) are touchscreen system coordinates. As thecalibration targets are displayed one by one on the touch display, theuser touches the calibration targets, resulting in measured touchscreencoordinates (x₁, y₁), (x₂, y₂), . . . (X₂₅, Y₂₅). In mathematicalnotation, for calibration target index k=1, 2, . . . 25, measuredtouchscreen coordinates (x_(k), y_(k)) correspond to display coordinates(X_(k), Y_(k)). Such calibration data is used to generate correctioncoefficients or parameters for run-time algorithms. The calibrationtargets may represent predetermined locations or calibration coordinateswithin the display coordinate system. Therefore, the calibration targetsneed not be displayed on a corresponding and/or attached display device.For example, during manufacturing an automated method may be used totouch the predetermined locations on the touchscreen prior to mountingthe touchscreen and the display device together. Examples of automatedmethods include a stencil, a bed-of-nails, an activation device that isrobotically controlled, and the like.

There are several options for extracting correction coefficients orparameters from the 25-point calibration data. For example thecalibration data could be used to construct look-up table data to beused in combination with linear interpolation. Polynomial expansions arealso used to generate mappings.

Polynomial expansions may be accomplished with respect to the center ofthe display. Let (x_(C),y_(C)) be the touchscreen coordinates generatedby a touch at the center of the touch display. Third-order polynomialexpansions for display coordinates (X,Y) in terms of touchscreencoordinates (x,y) are given by Equation (Eq.) 1 and 2 below. Eachequation contains ten monomial terms each with its own coefficient for atotal of twenty calibration constants A_(0,0), A_(1,0), A_(0,1),A_(2,0), A_(1,1), A_(0,2), A_(3,0), A_(2,1), A_(1,2), A_(0,3), B_(0,0),B_(1,0), B_(0,1), B_(2,0), B_(1,1), B_(0,2), B_(3,0), B_(2,1), B_(1,2)and B_(0,3). For example, polynomial coefficients may be computed fromthe calibration data (X_(k), Y_(k)) and (x_(k), y_(k)) for k=1 to 25.

$\begin{matrix}{X = {A_{0,0} + {A_{1,0} \cdot \left( {x - x_{C}} \right)} + {A_{0,1} \cdot \left( {y - y_{C}} \right)} + {A_{2,0} \cdot \left( {x - x_{C}} \right)^{2}} + {A_{1,1} \cdot \left( {x - x_{C}} \right) \cdot \left( {y - y_{C}} \right)} + {A_{0,2} \cdot \left( {y - y_{C}} \right)^{2}} + {A_{3,0} \cdot \left( {x - x_{C}} \right)^{3}} + {A_{2,1} \cdot \left( {x - x_{C}} \right)^{2} \cdot \left( {y - y_{C}} \right)} + {A_{1,2} \cdot \left( {x - x_{C}} \right) \cdot \left( {y - y_{C}} \right)^{2}} + {A_{0,3^{\cdot}}\left( {y - y_{C}} \right)}^{3}}} & {{Eq}.\mspace{14mu} 1} \\{Y = {B_{0,0} + {B_{0,1} \cdot \left( {x - x_{C}} \right)} + {B_{0,1} \cdot \left( {y - y_{C}} \right)} + {B_{2,0} \cdot \left( {x - x_{C}} \right)^{2}} + {B_{1,1} \cdot \left( {x - x_{C}} \right) \cdot \left( {y - y_{C}} \right)} + {B_{0,2} \cdot \left( {y - y_{C}} \right)^{2}} + {B_{3,0} \cdot \left( {x - x_{C}} \right)^{3}} + {B_{2,1} \cdot \left( {x - x_{C}} \right)^{2} \cdot \left( {y - y_{C}} \right)} + {B_{1,2} \cdot \left( {x - x_{C\;}} \right) \cdot \left( {y - y_{C}} \right)^{2}} + {B_{0,3} \cdot \left( {y - y_{C}} \right)^{3}}}} & {{Eq}.\mspace{14mu} 2}\end{matrix}$

For convenience, Eq. 3 and 4 assume that the touchscreen coordinateshave been offset to move the origin to the center, that is, x_(C)=0 andy_(C)=0. The general offset case may be returned to by the substitutionsx→(x−x_(C)) and y →(y−y_(C)).

X=A _(0,0) +A _(1,0) ·x+A _(0,1) ·y+A _(2,0) ·x ² +A _(1,1) ·xy+A _(0,2)·y ² +A _(3,0) ·x ³ +A _(2,1) ·x ² y+A _(1,2) ·xy ² +A _(0,3) ·y ³  Eq.3

Y=B _(0,0) +B _(1,0) ·x+B _(0,1) ·y+B _(2,0) ·x ² +B _(1,1) ·xy+B _(0,2)·y ² +B _(3,0) ·x ³ +B _(2,1) ·x ² y+B _(1,2) ·xy ² +B _(0,3) y ³  Eq. 4

The notation may be further simplified by using Σsummation notationwhere N=3 for the 3^(rd) order polynomial expansion of Eq. 3 and 4.

$\begin{matrix}{X = {\sum\limits_{m \geq {0n} \geq 0}^{{m + n} \leq N}{A_{m,n} \cdot x^{m} \cdot y^{n}}}} & {{Eq}.\mspace{14mu} 5} \\{{Y = {\underset{m \geq {0n} \geq 0}{\sum\limits^{{m + n} \leq N}}{B_{m,n} \cdot x^{m}}}}y^{n}} & {{Eq}.\mspace{14mu} 6}\end{matrix}$

Eq. 5 and 6 generalize to polynomial expansions of different ordersdepending on the value of N. For example, for values of N of 3, 5 and 7,the number of terms in each of the above equations is 10, 21 and 36respectively. For a 7^(th) order expansion, the total number ofcalibration constants A_(m,n) and B_(n,m) is 2*36=72, exceeding thenumber (2*25=50) of measured values x_(k) and y_(k) (k=1 to 25) from the25-point calibration process. In contrast, the number of constants for5^(th) and lower order polynomial expansions is less than the number of25-point calibration measurements.

The polynomial coefficients A_(m,n) and B_(n,m) may be determined bydoing a least squares fit. For any proposed set of polynomialcoefficients A_(m,n) and B_(n,m), one may compute the difference betweenX_(k), the known X coordinate of calibration target k used to displaythe calibration target, and the value of X computed above for thecorresponding measured touchscreen coordinates (x_(k), y_(k)). Thediscrepancy between actual and computed horizontal coordinates may benotated as ΔX_(k) and given by Eq. 7. ΔY_(k) may be similarly defined.

$\begin{matrix}{{\Delta \; X_{k}} = {X_{k} - {\overset{{m + n} \leq N}{\sum\limits_{m \geq {0n} \geq 0}}{A_{m,n} \cdot x_{k}^{m} \cdot y_{k}^{n}}}}} & {{Eq}.\mspace{14mu} 7}\end{matrix}$

The polynomial coefficients A_(m,n) and B_(n,m) may be determined byminimizing the sum of squares (SS) of Eq. 8, namely minimizing the SS ofthe discrepancies. (As the first sum depends only on the parametersA_(m,n) and the second sum only on the parameters B_(n,m), each sum canbe minimized separately with the same result.) Algorithms and code forsuch least squares fits are well known and widely available.

$\begin{matrix}{{SS} = {{\sum\limits_{k = 1}^{25}\left( {\Delta \; X_{k}} \right)^{2}} + {\sum\limits_{k = 1}^{25}\left( {\Delta \; Y_{k}} \right)^{2}}}} & {{Eq}.\mspace{14mu} 8}\end{matrix}$

This method for determining polynomial coefficients that are used tocalibrate the mapping between touchscreen coordinates (x,y) and displaycoordinates (X,Y) may be referred to as a conventional generalpolynomial fit to N^(th) order. Herein the conventional generalpolynomial fit may also be referred to as a conventional general fit. Aconventional general polynomial fit to 1^(st) order is a linear fit. A3^(rd) order conventional general polynomial fit is often sufficient tocorrect for slight bowing or pin-cushion non-linearities due tomanufacturing variations of a nominally linear touchscreen design.Higher order polynomial fits are desirable to handle strongernon-linearities such as those of picture-frame touchscreens. The25-point calibration process based on a conventional general polynomialfit is more powerful than the common 3-point linear calibration methodbut still has limitations.

In the conventional general polynomial fit, display coordinates (X,Y)are represented as polynomial expansions of the touchscreen coordinates(x,y). Such expansions are directly usable by run-time code thatreceives raw touchscreen coordinates (x,y) as input and generatesdisplay coordinates (X,Y) as output. Parameters from the polynomial fit,such as the monomial coefficients A_(m,n) and B_(n,m), may be directlystored by the calibration process for later use by run-time code duringoperation of the touch display system.

The conventional general polynomial fit severely limits the maximumorder of the polynomial expansion. For example, to keep the number ofcalibration constants smaller than the number of measurements from a25-point calibration grid, the order of the polynomial expansion must beno larger than five, that is, N≦5. Increasing the calibration grid to,for example, 9×9 results in a total of 2*81=162 measured values and mayallow expansions up to order N=11. However, with a 9×9 calibration grideach of the 81 calibration targets must be touched.

The above assumes that the calibration targets are touched with perfectaccuracy, which is almost never the case. Measured calibration data(x_(k), y_(k)) are subject to electronic noise. Additionally, impreciseactivation of touch calibration target locations may also result innoise. With noisy data, having a greater number of fit parameters canresult in a worse fit. In general, fits with high degrees of redundancy(many more data points than fit parameters) filter measurement noisewhile fits with low degrees of redundancy (number of data points notmuch larger than or equal to the number of fit parameters) amplifymeasurement noise particularly when extrapolating beyond the data range.

For a least squares fit of a polynomial expansion to 25-pointcalibration data, there are 25x measurements and 25 y measurements for atotal of 50 measured values. For the 3^(rd) order polynomial expansiondiscussed above, there are 10 fit parameters A_(m,n) and 10 fitparameters B_(n,m) for a total of 20 fit parameters. For 25-pointcalibration the redundancy is high (50 is much larger than 20) and thefitting process statistically averages out much of the calibrationmeasurement noise. In contrast, for a 5^(th) order polynomial expansion,there are 21 A_(m,n) parameters and 21 B_(n,m) parameters for a total of42. For 25-point calibration the redundancy is low (50 is not muchlarger than 42) and the fit makes poor predictions particularly whenextrapolating to locations outside the 5×5 grid. Hence in practice, even5^(th) order is problematic for a conventional general polynomial fit to25-point calibration data.

For picture-frame touchscreens, the 5×5 calibration grid can be expandedto be essentially the same size as the touch sensitive touch area. Thiseliminates the need to extrapolate to locations outside the calibrationgrid where conventional general polynomial fits tend to be mostproblematic. In contrast, for discrete-electrode touchscreens, theperimeter of the touch area is subject to complex local distortions asdiscussed above. The local distortions further add to the noise level ofthe touchscreen coordinates. To avoid this additional source of noise,all 5×5 calibration targets are positioned away from the perimeter andthus create a need for reliable extrapolation outside the 5×5calibration grid.

Therefore, a need exists for an improved calibration method for touchdisplay systems.

BRIEF DESCRIPTION OF THE INVENTION

In one embodiment, a method for calibrating a touch system comprisesdefining a set of calibration targets that have associated displaycoordinates (X_(i),Y_(i)) that are in a display coordinate system.Touchscreen coordinates (x_(i),y_(i)) that have noise are accepted. Eachof the touchscreen coordinates (x_(i),y_(i)) is associated with one ofthe calibration targets and the touchscreen coordinates are in atouchscreen coordinate system. Non-linear correction parameters arecomputed based on the touchscreen coordinates (x_(i),y_(i)) with respectto the display coordinates (X_(i),Y_(i)). The non-linear correctionparameters define a one-to-one correspondence between displaycoordinates (X,Y) and touchscreen coordinates (x,y) that is non-linear.The computing produces the one-to-one correspondence where an averagemagnitude of a Laplacian of at least one of x and y touchscreencoordinates with respect to the display coordinates is smaller than anaverage magnitude of a Laplacian of a one-to-one correspondence of aconventional general fit computed in the presence of the noise of thetouchscreen coordinates (x_(i),y_(i)). The Laplacians of the x and ytouchscreen coordinates are based on ∂²/∂X²+∂²x/∂Y² and ∂²y/∂X²+∂²y/∂y²,respectively.

In another embodiment, a computer readable medium for calibrating atouch system comprises instructions to detect touch points on atouchscreen. The touch points each are associated with touchscreencoordinates in a touchscreen coordinate system. The computer readablemedium also comprises instructions to associate each of the touch pointswith known calibration targets. Each of the calibration targets hasdisplay coordinates in a display coordinate system that is associatedwith at least one of a display screen and an operating system. Thecomputer readable medium further comprises instructions to fit thedisplay coordinates and the touchscreen coordinates non-linearly withrespect to each other based on a generalized Laplace-constrained fitthat is used to identify correction parameters used to map a usergenerated run-time touch point on the touchscreen to a displaycoordinate location on a display screen. The correction parametersrepresent non-linear corrections.

In yet another embodiment, a computer readable medium for calibrating atouch system comprises instructions to detect calibration touch pointson a touchscreen. The touch points each are associated with touchscreencoordinates in a touchscreen coordinate system. The computer readablemedium further comprises instructions to associate each of the touchpoints with known calibration targets that have display coordinates in adisplay coordinate system that is associated with a display screen. Thecalibration targets form an outline in the display coordinate system.The computer readable medium also comprises instructions to fit thedisplay coordinates and the touchscreen coordinates non-linearly withrespect to each other. The fit is used to identify correction parametersused to map touch points on the touchscreen to display coordinatelocations on the display screen.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a touch display formed in accordance with anembodiment of the present invention.

FIG. 2 illustrates a block diagram of a touch display system formed inaccordance with an embodiment of the present invention.

FIG. 3 illustrates a method of generating non-linear correctionparameters that are based on a generalized Laplace-constrained fitmethod in accordance with an embodiment of the present invention.

FIG. 4 illustrates a virtual calibration grid formed in accordance withan embodiment of the present invention.

FIG. 5 illustrates a calibration grid having calibration targets thatform an outline in accordance with an embodiment of the presentinvention.

FIG. 6 illustrates a table comparing a total number of fit parametersfor conventional general fits and Laplace-constrained fits in accordancewith an embodiment of the present invention.

FIG. 7 illustrates a first X excitation field map for a symmetric andlinear touchscreen formed in accordance with an embodiment of thepresent invention.

FIG. 8 illustrates a second X excitation field map for a symmetric andlinear touchscreen formed in accordance with an embodiment of thepresent invention.

FIG. 9 illustrates an example of a picture-frame touchscreen that issymmetrically designed and manufactured with tight manufacturingtolerances in accordance with an embodiment of the present invention.

FIG. 10 illustrates a touchscreen having a touch point in accordancewith an embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

The foregoing summary, as well as the following detailed description ofcertain embodiments of the present invention, will be better understoodwhen read in conjunction with the appended drawings. To the extent thatthe figures illustrate diagrams of the functional blocks of variousembodiments, the functional blocks are not necessarily indicative of thedivision between hardware circuitry. Thus, for example, one or more ofthe functional blocks (e.g., processors or memories) may be implementedin a single piece of hardware (e.g., a general purpose signal processoror random access memory, hard disk, or the like). Similarly, theprograms may be stand alone programs, may be incorporated as subroutinesin an operating system, may be functions in an installed softwarepackage, stored as instructions on a computer readable medium, and thelike. It should be understood that the various embodiments are notlimited to the arrangements and instrumentality shown in the drawings.

As used herein, an element or step recited in the singular and proceededwith the word “a” or “an” should be understood as not excluding pluralof said elements or steps, unless such exclusion is explicitly stated.Furthermore, references to “one embodiment” of the present invention arenot intended to be interpreted as excluding the existence of additionalembodiments that also incorporate the recited features. Moreover, unlessexplicitly stated to the contrary, embodiments “comprising” or “having”an element or a plurality of elements having a particular property mayinclude additional such elements not having that property.

Use of generalized Laplace constrained fits as discussed herein providea number of benefits relative to conventional general fits as a way tointerpolate and extrapolate from calibration data to a completeone-to-one correspondence between any display coordinate (X,Y) and anytouchscreen coordinate (x,y). For a given set of calibration targets,such as a 5 by 5 calibration target grid, and relative to conventionalgeneral fits, generalized Laplace constrained fits improve theinterpolation between the locations of the calibration targets andimprove extrapolation beyond the calibration targets. These improvementsresult from the use of the laws of physics to reduce the number ofindependent fit parameters. A reduced number of fit parameters increasesthe redundancy of the fit process and hence increases the ability of thefit to statistically average out calibration data errors due to varioussources of noise. Use of generalized Laplace constrained fits results inbetter calibration parameters for a given number of calibration targets,or alternately, allows equally good or better calibration parametersfrom a reduced number of calibration targets. One example of the latteris the case in which all interior targets are removed from a 5 by 5 grid(as shown in FIG. 5), reducing the number of targets from 25 to 16. Inthis case, even with only small amounts of calibration data noise, aconventional general fit interpolates to the center of the touchscreenin an erroneous fashion while a generalized Laplace fit interpolatesaccurately to the touchscreen center.

FIG. 1 illustrates a touch display 100 in accordance with an embodimentof the present invention. The touch display 100 may be other sizes andshapes. The touch display 100 may be installed on a desk, a wall, orwithin a kiosk, for example, or similar construction may used to form ahand-held device such as a personal digital assistant (PDA).

The touch display 100 comprises a touchscreen 102 and a display housing104. The touchscreen 102 is installed over a display screen (not shown).The display housing 104 may have a bezel width 106 extending over outeredges of the touchscreen 102 and the display screen.

FIG. 2 illustrates a block diagram of a touch display system 150 havinga touch display 154 interconnected with a computer 152. The touchdisplay 154 comprises components for displaying data on a display screen156. The display screen 156 may be an LCD, CRT, Plasma, OLED display,photographic image and the like. A touchscreen 158 is installed over thedisplay screen 156 and receives input from a user via a finger touch, astylus, and the like.

The computer 152 may include one or more of a linearity correctionmodule 188, a GUI module 192, a memory 194, a calibration module 196 andone or more run-time applications in an applications module 198. Thecomputer 152 may be used for acquiring non-linear correction parametersand/or calibration constants. The computer 152 may also apply thecorrection parameters and calibration constants during run-time toidentify locations of user touch events. In one embodiment, the computer152 may be used during the initial calibration of the touch displaysystem 150, such as during manufacture and/or assembly of the system150. In another embodiment, the computer 152 may be used to initiallycalibrate the touchscreen 158 prior to installing the touchscreen 158and the display screen 156 together. In yet another embodiment, thecomputer 152 may be used to run one or more run-time applications, suchas in a retail store, a restaurant, a factory for product testing, amedical facility and the like, and may optionally have the capability ofacquiring new correction parameters. For example, new correctionparameters may be needed if one or more components affecting linearitywere replaced in the touch display system 150. In addition to the touchdisplay 154, the computer 152 may comprise an alternate user input 184such as a keyboard and/or a mouse. Although indicated separately, thecomponents of the touch display system 150 may be within a single unit,such as a PDA or other portable device.

A display cable 160 connects the touch display 154 with a displaycontroller 162. The display controller 162 receives video informationfrom the computer 152 over video cable 164. The video information isreceived and processed by the display controller 162, then transferredto the touch display 154 over the display cable 160 for display on thedisplay screen 156. The touch display 154 and the display controller 162may be hardwired together or interconnected such that the display cable160 is not required. The display controller 162 comprises componentssuch as a CPU 166 and a memory 168.

A touchscreen cable 170 interconnects the touchscreen 158 with atouchscreen controller 172. The touchscreen controller 172 sends andreceives information to and from the computer 152 over touch data cable174. Touch information is received by the touchscreen 158, transferredover the touchscreen cable 170 to the touchscreen controller 172, andthen sent over the touch data cable 174 to the computer 152. Thetouchscreen controller 172 comprises components such as a CPU 178 andmemory 180.

A display housing (not shown) may enclose the touch display 154, thedisplay and touchscreen cables 160 and 170, and the display andtouchscreen controllers 162 and 172. As discussed in FIG. 1, the displayhousing may enclose an outer edge portion of the touchscreen 158,securing the touchscreen 158 and/or covering fasteners that secure thetouchscreen 158 to the display screen 156. The video and touch datacables 164 and 174 may be separate cables or packaged together. Thevideo and touch data cables 164 and 174 may extend from the displayhousing to the location of the computer 152. Optionally, the displayhousing may be a cover for a PDA or other small hand-held or portabledevice that may or may not hold the computer 152 there-within. Also, thetouch data cable 174 and video cable 164 may be replaced by wirelesstechnology.

In some embodiments, an outer edge portion or perimeter of thetouchscreen 158 may be designed as a dead region 186 to avoid falsetouches from the bezel contact on the surface of the touchscreen 158.For example, in typical resistive touchscreens, the dead region 186 mayextend slightly beyond the bezel towards the center of the touchscreen158 to avoid false touches due to bezel contact. Touch area 190 detectstouch events and may extend across the entire touchscreen 158 or toedges of the dead region 186.

The term “linearity” describes the ability of the touch display system150 to correctly map touch event coordinates that are in a touchscreencoordinate system with the actual coordinates of the underlying displayimage that are in a display coordinate system. To achieve goodlinearity, the touchscreen 158 is calibrated prior to run-time touchoperation. In one embodiment, the calibration module 196 may display aset of calibration targets on the display screen 156. For example, inthe 25-point calibration process, the user is asked to touch eachcalibration target within a 5×5 grid of displayed calibration targets.In another embodiment, the calibration module 196 may define the set ofcalibration targets that are the used by an automated process, such aswhen the touchscreen 158 is calibrated separate from the display screen156. The calibration module 196 generates a one-to-one correspondencebetween the touch event coordinates and the display coordinates andstores calibration data such as non-linear correction parameters,calibration constants and/or coefficients that may be stored in thememory 194 and used during run-time by the linearity correction module188.

During run-time, one or more applications within the applications module198 may be used with the GUI module 192 to display desired images on thedisplay screen 156. The Microsoft Windows® operating system is oneexample of a GUI module 192. The linearity correction module 188 detectsthe user touch points and uses the previously generated correctionparameters stored in the memory 194 to correlate the user touch pointsto cursor positions on the display screen 156, ensuring that thereaction of the touch display system 150 is linear. Coordinates of theuser touch point, corrected for touchscreen non-linearity using thepreviously determined parameters, are passed to the GUI module 192. TheGUI module 192 determines whether the coordinates indicate a selectionof a GUI button or icon. If a GUI button is selected, the computer 152may take further action based on the functionality associated with theparticular GUI button.

Although illustrated as separate modules, the functionality of thelinearity correction module 188, GUI module 192, calibration module 196and applications module 198 may be accomplished by a single portion offirmware or software, stored as instructions on a computer readablemedium (not shown) within and/or interconnected with the computer 152.Optionally, instructions to accomplish functions of the modules 188,192, 196 and 198, alone or together, may be stored within one or moremodules of firmware or software. Optionally, modules 188, 194 and 196may be located in touchscreen controller 172.

As discussed previously, the conventional general polynomial fit methodmay require more fit parameters than may be supported by the set ofcalibration targets. In other words, when the conventional generalpolynomial fit method uses higher order polynomials to determine thecoefficients, such as by going to 5^(th) or 7^(th) order polynomials,the number of fit parameters may either exceed the numbers of measuredquantities or may result in insufficient redundancy for reliableinterpolation and extrapolation. Not all polynomials allowed by aconventional general fit obey the laws of physics (such as Ohm's Law andKirchhoff's Junction Rule). Thus there is an opportunity to greatlyreduce the number of fit parameters by eliminating some or all of thefit parameters that do not obey the laws of physics, and hence providefits to calibration data with much improved reliability and accuracy.

FIG. 3 illustrates a method of generating non-linear correctionparameters that are based on a generalized Laplace-constrained fitmethod. The non-linear correction parameters describe a uniqueone-to-one correspondence between the display coordinates (X,Y) and thetouchscreen coordinates (x,y). Herein, the term “Laplace-constrainedfit” includes at least fits that apply to symmetric, quasi-symmetric andnon-symmetric touchscreens 158, as well as polynomial fits andLaplace-constrained fits that do not violate the laws of physics whenapplied to a uniform resistive coating. The term “quasi-symmetric” maybe used to refer to a touchscreen 158 that is symmetric in constructionbut is mounted with a tilt and/or offset with respect to the displayscreen 156. The term “generalized Laplace-constrained fit” includes atleast the Laplace-constrained fits as well as fits that may have a smallincrease in the number of fit parameters (compared to theLaplace-constrained fit) in order to account for non-uniformity of theresistive coating and perhaps other physical effects not accounted forin Laplace's equation.

Mathematically, the Laplace-constrained fit constrains the expansion,which in some cases may be a polynomial expansion, to obey the laws ofphysics and an assumption of resistive coating uniformity by consideringonly terms that satisfy Laplace's equation. The Laplace-constrained fitreduces the effects of noise in the calibration process (such aselectronic noise, inaccurate selection of the calibration targetlocation and local distortions), allows higher order polynomialexpansions (such as 7^(th) order), extrapolates more reliably outsidethe calibration grid and allows a reduction in the number of calibrationtargets that need to be touched. Therefore, compared to the conventionalgeneral fit, the Laplace-constrained fit reduces the fit parameters andresults in a better fit with the same data or a comparable fit with lessdata.

The improvements of the Laplace-constrained fit are also realized by thegeneralized Laplace-constrained fit in which the number of fitparameters is modestly increased (compared to the Laplace-constrainedfit) to account for resistive coating non-uniformity and perhaps otherphysical effects not accounted for in Laplace's equation. Thegeneralized Laplace-constrained fit also has a reduced number of fitparameters compared to the conventional general fit.

At 200, the calibration module 196 (as shown in FIG. 2) collectscalibration data. As was defined previously, (X,Y) indicates displaycoordinates and (x,y) indicates touchscreen coordinates that aredetected based on a user touch. The display coordinates (X,Y) may alsobe referred to as calibration coordinates that are associated with thedisplay screen 156 and/or the operating system within the GUI module192. Therefore, the use of display coordinates (X,Y) is not limited toapplications in which a display screen 156 is presently displaying theassociated calibration targets.

Initially, the 25-point calibration data based on a 5×5 grid ofcalibration targets will be discussed. The calibration module 196displays calibration targets that have a corresponding set of displaycoordinates (X,Y) on the display screen 156 and detects user generatedtouch points that have a corresponding set of touchscreen coordinates(x,y). The touchscreen coordinates (x,y) may be associated with atouchscreen coordinate system and the display coordinates (X,Y) may beassociated with a display coordinate system that is different than thetouchscreen coordinate system. In another embodiment, the calibrationdata need not be limited to a 5×5 grid and may be collected for adifferent number of calibration targets such as sixteen calibrationtargets in a 4×4 grid or 108 calibration targets in a 9×12 grid. In yetanother embodiment, the touchscreen 158 may be calibrated prior to beingmounted on the display screen 156. In this example, the displaycoordinates (X,Y) of each calibration target, also referred to ascalibration coordinates, are known and the touchscreen coordinates (x,y)may be generated in an automated environment. Many other arrangements ofcalibration targets are possible. However, by enabling more reliableinterpolation and extrapolation over larger distances, theLaplace-constrained fit method allows use of calibration grids withfewer calibration targets.

At 202, the calibration module 196 fits the calibration data togeneralized Laplace-constrained expansions of the touchscreencoordinates (x,y) in terms of the display coordinates (X,Y). In oneembodiment, a Laplace-constrained fit process involves a polynomialexpansion of the touchscreen coordinates (x,y) in terms of the displaycoordinates (X,Y). Thus, the output of 202 is a set of fit parametersthat defines a mapping from display coordinates (X,Y) to touchscreencoordinates (x,y). This mapping is in the opposite or inverse directioncompared to the conventional general fit that maps touchscreencoordinates (x,y) from finger touches to display coordinates (X,Y) usedby the operating system.

The GUI module 192 and applications module 198 operate based on displaycoordinates (X,Y). Therefore, at 204 the calibration module 196 invertsgeneralized Laplace-constrained expansions of touchscreen coordinates(x,y) in terms of display coordinates (X,Y) into expansions of thedisplay coordinates (X,Y) in terms of the touchscreen coordinates (x,y).

The polynomial expansions below express touchscreen coordinates (x,y) interms of display coordinates (X,Y). Also, α and β are used instead of Aand B, indicating mapping from display to touchscreen coordinates. Incontrast to the 20 independent fit parameters of a 3^(rd) orderconventional general fit as shown in Eq. 1 and 2, Eq. 9 and 10 have only14 fit parameters α_(X,0), α_(X,1), β_(X,1), α_(X,2), β_(X,2), α_(X,3),β_(X,3), α_(Y,0), α_(Y,1), β_(Y,1), α_(Y,2), β_(Y,2), α_(Y,3) andβ_(Y,3)

x=α _(X,0)·1+α_(X,1) ·X+β _(X,1) ·Y+α _(X,2)·(X ² −Y ²)+β_(X,2)·2XY+α_(X,3)·(X ³−3XY ²)+β_(X,3)·(3X ² Y−Y ³)  Eq. 9

y=α _(Y,0)·1+α_(Y,1) ·X+β _(Y,1) ·Y+α _(Y,2)·(X ² −Y ²)+β_(Y,2)·2XY+α_(Y,3)·(X ³−3XY ²)+β_(Y,3)·(3X ² Y−Y ³)  Eq. 10

Associated with each coefficient is a polynomial term that satisfiesLaplace's equation (as will be explained later). The polynomials 1, X,Y, (X²−Y²), 2XY, (X³−3X²Y) and (3XY²−Y³) are a complete list to 3^(rd)order of Laplace-constrained polynomials in the sense that any other3^(rd) order polynomial satisfying Laplace's equation is a linearcombination of these seven polynomials. X² is an example of a polynomialthat does not satisfy Laplace's equation and is hence eliminated fromconsideration by the seven-parameter expansions. Y² is also a polynomialthat does not satisfy Laplace's equation; however, X²−Y² does satisfyLaplace's equation and is equivalent to having a term X² with a fittedcoefficient α and also having a term Y² with no additional fit parameterbut rather a coefficient set to −α. For example, the fourth term of Eq.9 is α_(X,2)·(X²−Y²). Thus for every power k only four coefficients areallowed, two for x, namely α_(X,k) and β_(X,k), and two for y, namelyα_(Y,k) and β_(Y,k). Therefore, for polynomial expansions greater than1^(st) order the Laplace-constrained fit reduces the number of fitparameters. The higher the order, the more dramatic is the reduction.

Returning to 204, the calibration module 196 inverts the generalizedLaplace-constrained expansions (in this case Eq. 9 and 10) to produceexpansions for display coordinates (X,Y) in terms of touchscreencoordinates (x,y), as is needed by the run-time algorithms during normaloperation of the touch display system 150. One method of inversion is touse an expanded virtual calibration grid generated by using aLaplace-constrained fit to the measured calibration data. Other methods,such as algebraic expressions discussed later, may also be used and maybe referred to herein as “analytic method”.

FIG. 4 illustrates a 9×9 virtual calibration grid 220 with target indexk′=1, 2, . . . 81 and calibration target display coordinates (X_(k′),Y_(k′)). A first calibration target 222 corresponds to displaycoordinates (X₁, Y₁), a ninth calibration target 224 corresponds todisplay coordinates (X₉, Y₉), and an eighty-first calibration target 226corresponds to display coordinates (X₈₁, Y₈₁).

Once the Laplace-constrained fit parameters α_(X,0), α_(X,1), β_(X,1), .. . β_(Y,3) have been determined at 202 of FIG. 3 using measuredcalibration data (x_(k), y_(k)) where k=1, 2, . . . 25, at 204 thecalibration module 196 may use Eq. 11 and 12 below to predict “virtual”calibration data (x_(k′), y_(k′)) where k′=1, 2, . . . 81. It would beundesirable for the user to have to activate such a large number ofcalibration targets. However, the creation of the virtual calibrationdata (x_(k′), y_(k′)) is a computational step with no action required bythe user, and larger or smaller virtual grids may be used. For example,a very large calibration grid may generate results that may be used topopulate a look-up table.

x _(k′)=α_(X,0)·1+α_(X,1) ·X _(k′)+β_(X,1) Y _(k′)+α_(X,2)·(X _(k′) ² −Y_(k′) ²)+β_(x,2)·2X _(k′) Y _(k′)+α_(X,3)·(X _(k′) ³−3X _(k′) Y _(k′)²)+β_(X,3)·(3X _(k′) ² Y _(k′) −Y _(k′) ³)  Eq. 11

Y _(k′)=α_(Y,0)−1+α_(Y,1) ·X _(k′)+β_(Y,1) ·Y _(k′)+α_(Y,2)·(X _(k′) ²−Y _(k′) ²)+β_(Y,2)·2X _(k′) Y _(k′)+α_(Y,3)·(X _(k′) ³−3X _(k′) Y _(k′)²)+β_(Y,3)·(3X _(k′) ² Y _(k′) −Y _(k′) ³)  Eq. 12

Once the virtual calibration data is generated for a relatively largervirtual grid, the calibration module 196 computes non-linear correctionparameters, such as with a least squares fit as described for theconventional general polynomial fit in Eq. 1 and 2. In this example, thecoefficients are polynomial coefficients, such as coefficients A_(m,n)and B_(m,n). Using the generalized Laplace-constrained fit method ofFIG. 3, the problems associated with prior art conventional general fitsare avoided because the virtual calibration data for a large virtualcalibration grid that fills the touch area 190 provides the leastsquares fit with a high degree of redundancy and there is noextrapolation outside the data range.

At 206, the calibration module 196 stores in the memory 194 theresulting non-linear correction parameters 195, for example coefficientsA_(m,n) and B_(m,n) for use in run-time touch position calculations.Other representations and formats of non-linear correction parametersmay be used, such as monomial coefficients and/or look-up table(s), aswell as other mapping schemes, correlating touchscreen coordinates todisplay coordinates. The non-linear correction parameters describe theunique one-to-one correspondence between the display coordinates and thetouchscreen coordinates that satisfies Laplace's equation or onlyapproximately satisfies Laplace's equation to account for non-uniformityof the resistive coating and/or other physical effects.

Additionally, the calibration module 196 may store additionalcoefficients and/or parameters that may be used to apply additionalnon-linear or linear corrections. By way of example only, thetouchscreen 158 may be calibrated prior to be attached to the displayscreen 156. Therefore, the generalized Laplace-constrained fitparameters are known. An additional calibration, such as a 3-pointcalibration, may be accomplished by displaying three calibration targetson the display screen 156 to determine coordinate offsets and rotationalerror between the touchscreen 158 and the display screen 156. In anotherembodiment, coordinate offsets and rotational error may be known priorto mounting the touchscreen 158 and the display screen 156 together,resulting from processes during manufacturing and calibration.

The generalized Laplace-constrained fit creates calibration options thatare not possible with a conventional general polynomial fit. Previousfits, for example, needed interior calibration points. FIG. 5illustrates a calibration grid having calibration targets that form anoutline 231 within the touch area of the display coordinate system. Theoutline 231 may be of a rectangle, circle, square, substantially convexpolygon, and the like, and positions of the calibration targets maydeviate slightly from the outline 231 towards interior and exteriorareas with respect to the outline 231. In FIG. 5, 16-point calibrationgrid 230 has a set of calibration targets (X_(k), Y_(k)) configured in arectangular-shaped outline 231. The outline 231 may be, but is notnecessarily, proximate to the perimeter 238 of the touch area 190 of thetouchscreen 158 of FIG. 2. No calibration targets are located within aninterior area 239 with respect to the outline 231. In other words, theinterior area 239 is free of calibration targets. A first calibrationtarget 232 corresponds to display coordinates (X₁, Y₁), a secondcalibration target 234 corresponds to display coordinates (X₂, Y₂), anda sixteenth calibration target 236 corresponds to display coordinates(X₁₆, Y₁₆). Conventional general fits are very unreliable forcalibration grids that do not have interior points. In contrastgeneralized Laplace-constrained fits perform well with perimeter-onlycalibration grids used with either linear or non-linear types oftouchscreens 158. This is an example of the use of the generalizedLaplace-constrained fit to reduce the number of calibration targets,while at the same time maintaining or improving the performance of thecalibration process.

The outline 231 is not limited to a predetermined form, such as a circleor rectangle. In one embodiment, an inscribed circle 240 may bepositioned within all calibration targets. In other words, the inscribedcircle 240 is the largest centered circle whose interior contains nocalibration targets. A center 242 of the inscribed circle 240 may be thesame as a center of the display coordinate system and/or thetouchscreen. Radius 244 extends from the center 242 to the inscribedcircle 240. With respect to the outline 231, each of the calibrationtargets in the grid 230 are a distance away from a furthest closestneighboring calibration target that is less than the radius 244. Forexample, the first and second calibration targets 232 and 234 and thefirst and sixteenth calibration target 232 and 236 are separated by adistance that is less than the radius 244.

Calibration grids other than the 16-point calibration grid 230 may beused. For example, a minimum of 6 calibration targets may be arranged inthe display coordinate system to form an outline of a substantiallyconvex polygon, namely, a polygon whose interior angles are all lessthan 180 degrees. Deviations from the substantially convex polygon arecontemplated, and thus the arrangement of the calibration targets is notlimited. In addition, the calibration targets may be positioned in theoutline 231 in a relatively central location within the plane of thedisplay coordinate system or may be positioned closer or away from oneor more sides of the display coordinate system.

Referring again to 202 of FIG. 3, and initially focusing onLaplace-constrained fits that are a subset of the generalizedLaplace-constrained fit, the physical and mathematical basis of theLaplace-constrained expansions will be discussed in terms of a 5-wireresistive touchscreen 158. However, other types of touchscreens, such asa 9-wire resistive touchscreen or a capacitive touchscreen may be usedas well. The resistive coating on the glass substrate of a 5-wireresistive touchscreen is a continuous resistive network. Despite being acontinuous network, Ohm's Law and Kirchhoff's Junction Rule ofelectronics still apply.

Ohm's Law is typically expressed as “voltage equals current timesresistance”. However, as is well known, for a resistive coating Ohm'sLaw takes the vector calculus form “voltage gradient equals minuscurrent density times resistivity” (or equivalently “current densityequals conductivity times the electric field” where conductivity is theinverse of resistivity and the electric field is minus the voltagegradient). Thus, in symbolic form, Ohm's Law for a continuous resistivecoating takes the form −∇V=ρJ where the 2-D vector ∇ is the gradientoperator (∂/∂X, ∂/∂Y) and the 2-D vector J is the surface currentdensity (J_(x),J_(y)).

Kirchhoff's Junction Rule states that the sum of currents entering anelectrical junction equals the sum of currents exiting the electricaljunction. Kirchhoff's rule is a statement of charge conservation forsteady state currents. Applied to a continuous resistive coating, chargeconservation for steady state currents is expressed as “the divergenceof current density is zero.” In the notation of vector calculus, this issymbolically stated as ∇·J=0.

Kirchhoff's Junction Rule in the form ∇·J=0 may be combined with Ohm'sLaw in the form −∇V=ρJ as follows. Taking the divergence of both sidesof Ohm's Law results in −∇²V=−∇·∇V=∇·(ρJ)=(∇ρp)·J+ρ(∇·J) where theLaplacian operator ∇² is equal to ∂²/∂X²+∂²/∂Y². By applying chargeconservation ∇·J=0, this reduces to −∇²V=(∇ρ)·J and becomes Eq. 13 afteragain using Ohm's Law in the form J=−(∇V)/ρ.

∇² V={(∇ρ)/ρ}·∇V  Eq. 13

If the resistive coating is uniform, then the resistivity gradient ∇ρ iszero and Eq. 13 reduces differential equation, Eq. 14, which is known asLaplace's Equation. This is true for both X gradient and Y gradientexcitations.

∇² V=∂ ² V/∂X ²+∂² V/∂Y ²=0  Eq. 14

Let x(X,Y) be the raw (uncorrected) x coordinate as a function ofdisplay coordinates (X,Y) from the 5-wire touchscreen. Within possibleoffset and scaling factors, x(X,Y) is the voltage for an X excitation onthe glass substrate's resistive surface as a function of position. Hencex(X,Y) must satisfy Laplace's Equation. For similar reasons, the raw ytouchscreen coordinate y(X,Y) also satisfies Laplace's Equation.

∇² x(X,Y)=∂² x/∂X ²+∂² x/∂Y ²=0  Eq. 15

∇² y(X,Y)=∂² y/∂X ²+∂² y/∂Y ²=0  Eq. 16

Therefore, at 202 of FIG. 3, the number of fit parameters may be greatlyreduced by considering only expansions of touchscreen coordinates (x,y)in terms of display coordinates (X,Y) that satisfy at least one of Eq.15 and 16 and hence also satisfy the laws of physics (Ohm's Law andKirchhoff's Junction Rule) for current flow through uniform resistivecoatings. In other words, the Laplacian of at least one of the x and ytouchscreen coordinates with respect to the display coordinates (X,Y) issmaller than an average magnitude of a Laplacian of a one-to-onecorrespondence computed with the conventional general fit, especiallyfor noisy touchscreen coordinate data.

It can be verified that each term of the above Laplace expansionx=α_(X,0)·1+α_(X,1)X+β_(X,1)·Y+α_(X,2)·(X²−Y²)+ . . . +β_(X,3)·(3XY²−Y³)satisfies Laplace's Equation. For example the Laplacian of the fourthterm (X²−Y₂) is zero, that is ∇²(X²−Y²)=∇²X²−∇²Y²=2−2=0. For higherorder Laplace expansions, it is convenient to have a systematic methodfor finding terms that satisfy Laplace's Equation. This can be done byusing the complex number notation Z=X+iY and observing that 1=Re{Z⁰},X=Re{Z¹}, Y=Im{Z¹}, (X²−Y²)=Re{Z²}, 2XY=Im{Z²}, (X³−3X²Y)=Re{Z³} and(3XY²−Y³)=Im{Z³}. For example Z²=(X+iY)²=(X²−Y²)+i·2XY which has a realcomponent of (X²−Y²) and an imaginary component of 2XY. Thus for N=3,the above Laplace-constrained expansions for 202 of FIG. 3 can berewritten as follows.

$\begin{matrix}{x = {{\sum\limits_{n = 0}^{N}{{\alpha_{X,n} \cdot {Re}}\left\{ \left( {X + {\; Y}} \right)^{n} \right\}}} + {\sum\limits_{n = 1}^{N}{{\beta_{X,n} \cdot {Im}}\left\{ \left( {X + {\; Y}} \right)^{n} \right\}}}}} & {{Eq}.\mspace{14mu} 17} \\{y = {{\sum\limits_{n = 0}^{N}{{\alpha_{Y,n} \cdot {Re}}\left\{ \left( {X + {\; Y}} \right)^{n} \right\}}} + {\sum\limits_{n = 1}^{N}{{\beta_{Y,n} \cdot {Im}}\left\{ \left( {X + {\; Y}} \right)^{n} \right\}}}}} & {{Eq}.\mspace{14mu} 18}\end{matrix}$

Eq. 17 and 18 represent Laplace-constrained polynomial expansions to anyorder N. For example, Laplace-constrained expansions to fifth orderinclude the terms proportional to the fifth order polynomialsRe{Z⁵}=(X⁵−10−X³Y²+5 ·XY⁴) and Im{Z⁵}=(5·X⁴Y−10·X²Y³+Y⁵). In anotherembodiment, the above polynomial expansions may be altered, for example,by replacing the basis polynomials Re{(X+iY)^(n)} and Im{(X+iY)^(n)}with various linear combinations of these basis polynomials.

In another embodiment, the Laplace constrained polynomial Eq. 17 and 18may be rewritten in polar coordinates with radius R and polar angle φ asshown in Eq. 19 and 20. In polar coordinates Z=(X+iY)=R·e^(iφ) and henceZ^(n)=(X+iY)^(n)=R^(n)·e^(inφ) so that Re{Z^(n)}=R^(n)·cos(nφ) andIm{Z^(n)}=R^(n)·sin(nφ).

$\begin{matrix}{x = {{\sum\limits_{n = 0}^{N}{\alpha_{X,n} \cdot R^{n} \cdot {\cos \left( {n\; \varphi} \right)}}} + {\sum\limits_{n = 1}^{N}{\beta_{X,n} \cdot R^{n} \cdot {\sin \left( {n\; \varphi} \right)}}}}} & {{Eq}.\mspace{14mu} 19} \\{y = {{\sum\limits_{n = 0}^{N}{\alpha_{Y,n} \cdot R^{n} \cdot {\cos \left( {n\; \varphi} \right)}}} + {\sum\limits_{n = 1}^{N}{\beta_{Y,n} \cdot R^{n} \cdot {\sin \left( {n\; \varphi} \right)}}}}} & {{Eq}.\mspace{14mu} 20}\end{matrix}$

The fit parameters α_(X,n) and β_(X,n) are thus interpreted as theFourier series coefficients of the X excitation potential x(R,φ)=V(R,φ)on the perimeter of a circle of unit radius centered on the origin.

FIG. 6 compares the total number of fit parameters for conventionalgeneral fits and Laplace-constrained fits as a function of the order Nof the polynomial fit. Column 270 is the polynomial order N, column 272is the number of fit parameters for the associated polynomial order forthe conventional general polynomial fit, column 274 is the number of fitparameters of the associated polynomial order for theLaplace-constrained fit, and column 276 is the difference in the numberof fit parameters between the conventional general fit (column 272) andLaplace-constrained fit (column 274), or the number of fit parametersthat are eliminated. Column 340 is the number of fit parameters for theassociated polynomial order for a symmetric Laplace-constrained fit thatis discussed further below.

Because the number of conventional general fit parameters (column 272)grows quadratically with N, equaling (N+2)(N+1), while the number ofLaplace-constrained fit parameters (column 274) grows only linearly withN, equaling (4N+2), the relative advantage of the Laplace-constrainedfit increases with increasing polynomial order N (column 270). Forexample, for a fifth order expansion 278, the Laplace-constrained fitreduces the number of fit parameters by about a factor of 2, fromforty-two conventional general fit parameters 280 to twenty-twoLaplace-constrained fit parameters 282. If the Laplace-constrained fitis generalized to account for possible non-uniformities in the resistivecoating, additional fit parameters are introduced, and hence the numbersin columns 274 and 340 become lower limits and the difference numbers incolumn 276 become upper limits. However, as long as the number ofadditional parameters is small, the fit redundancy advantages ofLaplace-constrained fits are largely retained.

Because of noise in data, the conventional general fit will producenon-zero values for correction parameters that violate the laws ofphysics and give distortions that are not present in the touchscreen158. In other words, the one-to-one correspondence computed with aconventional general fit will result in larger values compared to theone-to-one correspondence computed where a Laplacian of at least one ofthe x and y touchscreen coordinates is small, zero or substantially zero(see Eq. 15 and 16). The Laplace-constrained fit prevents noise anderrors in the data from generating coefficients that are not allowed tobe there by the laws of physics. Therefore, the 3^(rd) order fit resultsin a better fit because there is a higher level of redundancy. Also, theseventh order fit may be accomplished with a generalizedLaplace-constrained fit but not with the conventional general fit to25-point calibration data.

In one embodiment, only terms satisfying Laplace's equation are allowedin the expansion at 202 of FIG. 3. However, in another embodiment, some,but not all, fit parameters corresponding to terms that violateLaplace's Equation may be allowed. In other words, one or moreconventional general fit parameters from the column 272 that are notincluded within the Laplace-constrained fit parameters of column 274 maybe used. Any reduction of fit parameters with the use of Laplace'sequation provides benefits; however, in some cases it may beadvantageous to include one or more terms that violate Laplace'sequation.

As discussed previously, Laplace's equation results from the assumptionthat the resistivity of the coating (e.g. ITO) is uniform, that is, theresistivity gradient ∇ρ is zero. Now the possibility of a small butnon-zero resistivity gradient is considered, particularly, a small anduniform gradient of unknown direction and magnitude. One example of anon-uniform gradient is a gradual change in resistivity from one side ofthe touchscreen 158 to the other. For example, the ITO coating maygradually become more resistive when going from the left to right acrossthe touch area 190. In this case the laws of physics lead to theequation ∇²V={(∇ρ)/ρ}·∇V≠0. The deviation from Laplace's equation ∇²V=0is proportional to the magnitude of the resistivity gradient. In thecase that the touchscreen 158 is close to being linear, the quantity{(∇ρ)/ρ}·∇V may be estimated to a first approximation. For the Xexcitation of an approximately linear touchscreen 158, the voltagegradient is dominated by the linear term in the polynomial expansion and∇V=∇x≈(α_(X,1), 0). Likewise, the estimate ∇V=∇y≈(0, β_(Y,1)) may beused for the Y excitation. Hence for the X excitation{(∇ρ)/ρ}·∇V≈α_(X,1)·(1/ρ)·∂ρ/αX and for Y excitation{(∇ρ)/p}·∇V≈β_(Y,1)·(1/ρ)·∂ρ/∂Y. Thus, to a better approximation thanLaplace's equation, applying the laws of physics leads to Eq. 21 and 22that take into account a resistive coating non-uniformity in the form ofa resistivity gradient.

∇² x≈α _(X,1)·(1/ρ)·∂ρ/∂X  Eq. 21

∇² y≈β _(Y,1)·(1/ρ)·∂ρ/∂Y  Eq. 22

Eq. 21 and 22 result in the introduction of a new polynomial term 65_(X)·X²/2 to the x expansion and a new polynomial term γ_(y)·Y²/2 to they expansion, respectively. The fit will tend to adjust the new fitparameters γ_(X) and γ_(Y) to the values α_(X,1)·(1/ρ) ∂ρ/∂X andβ_(Y,1)·(1/ρ) ∂ρ/∂Y, respectively, as the true voltage gradients satisfythe above equations better than Laplace's equation. By adding twoparameters to accommodate for non-uniformities in resistivity, some ofthe redundancy of the fit is lost. Nevertheless, this modification of aLaplace-constrained fit results in a generalized Laplace-constrained fitthat provides more fit redundancy than a conventional general fit. Forexample, for a 3^(rd) order fit, the modified Laplace expansion (Eq. 21and 22) has 16 parameters (two more parameters in comparison with theLaplace-constrained fit). This is a significant reduction with respectto the 20 parameters of a conventional general fit to 3^(rd) order. Eq.23 and 24 are modifications of Eq. 17 and 18, respectively, accountingfor the additional terms accommodating resistive coatingnon-uniformities as discussed.

$\begin{matrix}{x = {{\sum\limits_{n = 0}^{N}{{\alpha_{X,n} \cdot {Re}}\left\{ \left( {X + {\; Y}} \right)^{n} \right\}}} + {\sum\limits_{n = 1}^{N}{{\beta_{X,n} \cdot {Im}}\left\{ \left( {X + {\; Y}} \right)^{n} \right\}}} + {\gamma_{X} \cdot {X^{2}/2}}}} & {{Eq}.\mspace{14mu} 23} \\{y = {{\sum\limits_{n = 0}^{N}{{\alpha_{Y,n} \cdot {Re}}\left\{ \left( {X + {\; Y}} \right)^{n} \right\}}} + {\sum\limits_{n = 1}^{N}{{\beta_{Y,n} \cdot {Im}}\left\{ \left( {X + {\; Y}} \right)^{n} \right\}}} + {\gamma_{Y} \cdot {Y^{2}/2}}}} & {{Eq}.\mspace{14mu} 24}\end{matrix}$

While the expressions of Equations 23 and 24 violate Laplace's equationfor small values of γ_(X) and γ_(Y) corresponding to mild resistivitygradients, the degree of violation is small compared to that of therelation between touchscreen and display coordinates provided by aconventional general fit. The degree of violation of Laplace's equationis quantified by averaging the magnitude of the Laplacian over displaycoordinates (X,Y) corresponding to the touch sensitive area of thetouchscreen. If the touch sensitive area of the touchscreen correspondsto (X,Y) coordinates in the ranges Xmin<X<Xmax and Ymin<Y<Ymax, then theaverage magnitude of the Laplacian of the touchscreen x coordinate maybe computed with the following double integral expressions or suitableapproximations as double sums.

$\begin{matrix}{\int_{X\; \min}^{X\; \max}{\int_{Y\; \min}^{Y\; \max}{{{\nabla^{2}{x\left( {X,Y} \right)}}}{{X}/\left( {{X\; \max} - {X\; \min}} \right)}{{Y}/\left( {{Y\; \max} - {Y\; \min}} \right)}}}} & {{Eq}.\mspace{14mu} 25} \\{\int_{X\; \min}^{X\; \max}{\int_{Y\; \min}^{Y\; \max}{{{\nabla^{2}{y\left( {X,Y} \right)}}}{{X}/\left( {{X\; \max} - {X\; \min}} \right)}{{Y}/\left( {{Y\; \max} - {Y\; \min}} \right)}}}} & {{Eq}.\mspace{14mu} 26}\end{matrix}$

In Eq. 25 and 26, ∇²x(X,Y)=∂x/∂X²+∂²x/∂Y² and ∇²y(X,Y)=∇²y/∂X²+∂²y/∂Y².In the case that x(X,Y) and y(X,Y) are given by Equations 23 and 24above, the expressions of Eq. 25 and 26 for average magnitudes of theLaplacian are evaluated to be simply γ_(X) and γ_(Y) respectively andtypically less than 10% of corresponding average magnitudes of theLaplacian for a convention general fit.

Laplace's equation and the analysis above assumes that the displaycoordinates system of the display screen 156 is a Cartesian coordinatesystem. This is the case if X and Y are measured in units of pixels andthe pixel pitch (e.g. 0.27 mm) is the same in the vertical andhorizontal directions. However, in one embodiment non-Cartesiancoordinate systems may be used, such as in programming, in which X and Ycoordinates are scaled differently. This is the case, for example, X andY may be scaled to the same two-byte signed integer range from −32,768to +32,767 even when the display height to width aspect ratio is 3:4.The above equations may thus be modified for the case of non-Cartesiandisplay coordinates, wherein the non-Cartesian display coordinates areindicated as (X′,Y′). Let S_(X) and S_(Y) be scaling factors betweennon-Cartesian coordinates (X′,Y′) and some Cartesian display coordinates(X,Y) such that X=S_(x)·X′ and Y=S_(Y)·Y′. The substitutions X→S_(X)·X′and Y→S_(Y)·Y′ may be made into the above equations and the laws ofphysics remain satisfied.

In terms of the non-Cartesian coordinates (X′,Y′), the Laplacianexpressions can be written as ∇²x(X′,Y′)=(1/S_(X) ²)*∂²x/∂X′²+(1/S_(Y)²)*∂²x/∂Y′² and ∇²y(X′,Y′)=(1/S_(X) ²)*∂²y/∂X′²+(1/S_(Y) ²)*∂²y/Y′². Asis well know in mathematical physics, the Laplacian can similarly begeneralized to a number of coordinate systems, i.e. curvilinearcoordinate systems that are not Cartesian.

The origin of the (Cartesian) display coordinate system also needs to bedetermined. The above derivations are correct regardless of the locationof the origin. In varying embodiments, the point (X,Y)=(0,0) may be thecenter of the display screen 156, the lower left corner of the displayscreen 156 or anywhere else in the plane of the display screen 156. Inpractice, an origin close to or at the center of the display screen 156may be desirable as the polynomial expansions converge much faster withthe origin being near the symmetry point of the display screen 156 andtouch area 190 of the touchscreen 158. Because the finite number ofcalibration targets supports polynomial expansions of only limitedorders, rapid convergence is desired and may be achieved by centering ator near the origin. Likewise, it is generally advantageous forpolynomial expansions to have a centered origin for the touchscreencoordinates (x,y). However, it is not necessary for the origin to becentered.

Due to symmetries in the design of touch display system 150, many of thecoefficients in fitted Laplace expansions such asx=α_(X,0)·1+α_(X,1)·X+β_(X,1)·Y+α_(X,2)·(X²−Y²)+ . . .+β_(X,3)·(3XY²−Y³) tend to be small. Symmetries may be left/rightsymmetries or top/bottom symmetries, for example. If manufacturingvariations are sufficiently small, the symmetries may allow eliminationof one, several or many terms from the polynomial expansions. Oneexample of symmetries is the case when manufacturing variations arenearly or completely negligible.

FIGS. 7 and 8 consider X excitation field maps for the case of an idealsymmetric and perfectly linear touchscreen 260. Both FIGS. 7 and 8represent the same touchscreen 260 with the same voltage excitation ofthe resistive coating on the glass substrate. At the four corners of thetouchscreen 260 are written the excitation voltages asserted byassociated touchscreen controller electronics (not shown). In FIG. 7,the corners are indicated as top left corner 280, bottom left corner282, top right corner 284, and bottom right corner 286. In FIG. 8, thecorners are indicated as top left corner 288, bottom left corner 290,top right corner 292, and bottom right corner 294.

In FIG. 7, touchscreen ground or zero volts is defined by the analogcircuit ground of the controller electronics so that the top and bottomleft corners 280 and 282 are grounded to zero volts and the top andbottom right corners 284 and 286 are powered at a voltage level, in thiscase, 5 volts. The touchscreen 260 has a touch area 296 surrounded byperimeter electrodes 298 that are schematically shown by shading. Dottedlines 300, 302, 304 and 306 represent lines of constant voltage of 1volts, 2 volts, 3 volts and 4 volts, respectively, resulting from the Xexcitation. In addition, X axis 308 and Y axis 310 represent a displaycoordinate system whose origin 312 is centered on the display screen 156(not shown). In this example, it is assumed that the touch area 296 andperimeter electrodes 298 of the touchscreen 260 are symmetric in designand manufacture as well as being perfectly aligned with respect to thedisplay screen 156.

In FIG. 7 the voltage at the origin 312, wherein (X,Y)=(0,0), is 2.5volts as the origin 312 is located midway between lines 302 and 304.Turning to FIG. 8, ground or zero volts is defined as the voltage at theorigin 312. With this definition of ground for FIG. 8, the top andbottom left corners 288 and 290 are excited with −2.5 volts, the top andbottom right corners 292 and 294 are excited with +2.5 volts, and linesof constant voltage, lines 314, 316, 318 and 320, correspond to −1.5volts, −0.5 volts, +0.5 volts and +1.5 volts, respectively. The rawtouchscreen coordinate x=x(X,Y) is defined to be the local resistivecoating voltage as defined in FIG. 8. By avoiding artificial asymmetriesin the coordinate system definitions and ground definition, symmetriesof the hardware become more apparent. In general, the electrostaticpotential x(X,Y) for the X excitation of touchscreen 260 in FIG. 8 isanti-symmetric in X and symmetric in Y. In particular, the horizontaltouchscreen coordinate x is an anti-symmetric function of the horizontaldisplay coordinate X:

x(−X,Y)=−x(X,Y)  Eq. 27

and at the same time a symmetric function of vertical display coordinateY:

x(X,−Y)=+x(X,Y)  Eq. 28

In a similar fashion, for perfectly symmetric touch display hardware,the vertical touchscreen coordinate y satisfies the symmetry relations:

y(−X,Y)=+y(X,Y)  Eq. 29

y(X,−Y)=−y(X,Y)  Eq. 30

The above symmetry relations also apply to non-linear touchscreens 158provided that the touch display system 150 is still symmetric. FIG. 9illustrates an example of a picture-frame touchscreen 330 that issymmetrically designed and manufactured with tight manufacturingtolerances. For example, a (simulated) Y-excitation shown using multiplelines of constant potential 332 satisfies the above symmetry relations.Another example is a nominally linear touchscreen (not shown) that has aslight symmetric pin-cushion distortion due to manufacturing variations.When the touchscreen design and the nature of anticipated manufacturingvariations preserve the symmetries, the above symmetry relations providean opportunity to further reduce the number of fit parameters.

With the above symmetry relations in mind, consider again the Laplaceexpansions of, for example, Eq. 9 and 10. Many terms in the expansionx=α_(X,0)·1+α_(X,1)·X+β_(X,1)·Y+α_(X,2)·(X²−Y₂)+ . . .+β_(X,3)·(3XY²−Y³) violate the symmetry relations of Eq. 27 and 28. Theterms α_(X,0)·1, β_(X,1)·Y, α_(X,2)·(X²−Y²) and β_(X,3) ·(3X²Y−Y³) arehorizontally symmetric in the sense that they are unaffected by thereplacement X→−X. These terms are not horizontally anti-symmetric asrequired by the symmetry relation x(−X,Y)=−x(X,Y). Thus, in oneembodiment, the coefficients α_(X,0), β_(X,1), α_(X,2) and β_(X,3) mustall be zero. The terms β_(X,1)·Y, β_(X,2)·2XY and β_(X,3)·(3X²Y−Y³) arevertically anti-symmetric in violation of the vertical symmetryrequirement x(X,−Y)=x(X,Y), and thus the coefficients β_(X,1), β_(X,2)and β_(X,3) must also be zero. Therefore, the complete Laplace expansionof proper symmetry to 3^(rd) order is x=α_(X,1)·X+α_(X,3)·(X³−3XY²).Symmetry has thus reduced the number of terms from seven to two.Likewise symmetry reduces the generalized Laplace-constrained expansionfor the vertical touchscreen coordinate toy=β_(Y,1)·Y+β_(Y,3)·(3X²Y−Y³). The non-zero coefficients for the xexpansion only include the α_(X,n) coefficients for odd values of n,such as n=1, 3, 5, . . . . The y expansions only includes β_(Y,n)coefficients for odd values of n. Generalizing to an arbitrary order N,Eq. 31 and 32 give the symmetric Laplace expansions.

$\begin{matrix}{x = {\overset{n \leq N}{\sum\limits_{n\mspace{11mu} {odd}}}{{\alpha_{X,n} \cdot {Re}}\left\{ \left( {X + {\; Y}} \right)^{n} \right\}}}} & {{Eq}.\mspace{14mu} 31} \\{y = {\overset{n \leq N}{\sum\limits_{n\mspace{11mu} {odd}}}{{\beta_{Y,n} \cdot {Im}}\left\{ \left( {X + {\; Y}} \right)^{n} \right\}}}} & {{Eq}.\mspace{14mu} 32}\end{matrix}$

In another example, Eq. 33 and 34 may be used for a 7^(th) orderexpansion (N=7).

x=α _(X,1) ·X+α _(X,3)·(X ³−3XY ²)+α_(X,5)·(X ⁵−10X ³ Y ²+5XY⁴)+α_(X,7)·(X ⁷−21X ⁵ Y ²+35X ³ Y ⁴−7XY ⁶)  Eq. 33

y=β _(Y,1) ·Y+β _(Y,3)·(3X ² Y−Y ³)+β_(Y,5)·(5X ⁴ Y−10X ² Y ³ +Y⁵)+β_(Y,7)·(7X ⁶ Y−35X ⁴ Y ³+21X ² Y ⁵ Y ⁷)  Eq. 34

One or more constants may be added to Eq. 31, 32, 33 and 34, forexample, to account for an asymmetric ground definition as is shown inFIG. 7.

Returning to FIG. 6, column 340 is the number of fit parameters for theassociated polynomial order for a symmetric Laplace-constrained fit.Even compared to the number of fit parameters of the Laplace-constrainedfit shown in column 274, the symmetric Laplace-constrained fitdramatically reduces the number of fit parameters.

In another embodiment, the touch display system 150 may be constructedin a symmetric fashion, but a slight offset exists between the center ofthe touchscreen 158 and the center of the display screen 156. This mayoccur due to a registration error when the touchscreen 158 is mountedonto the display screen 156. Also, even if the touch display hardware isperfectly symmetric, if the user does not view the touch display 100from an angle perpendicular to the plane of the display screen 156 (suchas when the calibration data is collected at 200 of FIG. 3), parallaxeffects will cause an offset between the true center of the touchscreen158 and the point on the touchscreen 158 that appears to be in front ofthe center of the display screen 156. For example, let (X₀, Y₀) be thedisplay coordinates of the display image pixel that is perceived by theuser to be directly below the exact center of the touch area 190 of thetouchscreen 158.

Eq. 35 and 36 extend the symmetric Laplace-constrained fit (Eq. 31 and32) to the case of a non-zero touchscreen-display offset (X₀, Y₀). Thisis one example of a quasi-symmetric Laplace-constrained fit. Thequasi-symmetric Laplace-constrained fit assumes that the touchscreen 158is perfectly symmetric but may be asymmetrically mounted on the touchdisplay 154. In the fitting process, the coordinate offsets X₀ and Y₀are regarded as unknown parameters to be determined by the fit. Theaddition of two more fit parameters somewhat reduces the redundancy ofthe symmetric Laplace-constrained fit. Nevertheless, the quasi-symmetricLaplace-constrained fit of Eq. 35 and 36 has a greatly reduced number offit parameters than both the generalized Laplace-constrained fit and theconventional general fit.

$\begin{matrix}{x = {\overset{n \leq N}{\sum\limits_{n\mspace{11mu} {odd}}}{{\alpha_{X,n} \cdot {Re}}\left\{ \left\lbrack {\left( {X - X_{0}} \right) + {\left( {Y - Y_{0}} \right)}} \right\rbrack^{n} \right\}}}} & {{Eq}.\mspace{14mu} 35} \\{y = {\overset{n \leq N}{\sum\limits_{n\mspace{11mu} {odd}}}{{\beta_{Y,n} \cdot {Im}}\left\{ \left\lbrack {\left( {X - X_{0}} \right) + {\left( {Y - Y_{0}} \right)}} \right\rbrack^{n} \right\}}}} & {{Eq}.\mspace{14mu} 36}\end{matrix}$

For the specific case of a 3^(rd) order expansion, Eq. 35 and 36 reduceto the explicit equationsx=α_(X,1)·(X−X₀)+α_(X,3)·{(X−X₀)³−3·(X−X₀)·(Y−Y₀)²} andy=β_(Y,1)·(Y−Y₀)+β_(Y,3)·{3·(X−X₀)²·(Y−Y₀)−(Y−Y₀)³}, respectively.

The symmetric Laplace-constrained fit (Eq. 31 and 32) can be modifiedfurther to accommodate a possible small rotation of the touchscreenrelative to the display. In some cases, the small rotation may be aresult of manufacturing and/or assembly and may not affect the end-userapplication. However, if the application has tight tolerances, such assmall touchscreen buttons that are close together and/or a smalltouchscreen with limited room for display, it may be desirable tocompensate for the rotation. Let δθ be the relative rotation between thetouchscreen 158 and display screen 156. The δθ may serve as anadditional fit parameter, such as in the polynomial expansions of Eq. 37and 38, with exp(−iδθ)=cos(δθ)−i·sin(δθ). Eq. 37 and 38 also areexamples of a quasi-symmetric Laplace-constrained fit. The expressionsare evaluated with the usual rules for multiplying complex numbers.

$\begin{matrix}{x = {\overset{n \leq N}{\sum\limits_{n\mspace{11mu} {odd}}}{{\alpha_{X,n} \cdot {Re}}\left\{ \left( {{\exp \left( {{- {\delta}}\; \theta} \right)} \cdot \left\lbrack {\left( {X - X_{0}} \right) + {\left( {Y - Y_{0}} \right)}} \right\rbrack} \right)^{n} \right\}}}} & {{Eq}.\mspace{14mu} 37} \\{y = {\overset{n \leq N}{\sum\limits_{n\mspace{11mu} {odd}}}{{\beta_{Y,n} \cdot {Im}}\left\{ \left( {{\exp \left( {{- {\delta}}\; \theta} \right)} \cdot \left\lbrack {\left( {X - X_{0}} \right) + {\left( {Y - Y_{0}} \right)}} \right\rbrack} \right)^{n} \right\}}}} & {{Eq}.\mspace{14mu} 38}\end{matrix}$

The above fit parameters X₀, Y₀ and δθ enter into Eq. 37 and 38 in anon-linear fashion. This may be a problem for the simplest code forcomputing least squared fits. However, more powerful fit algorithms arewell known that are capable of performing fits based in Eq. 37 and 38.

In Eq. 39 and 40, α′_(X,n) and β′_(Y,n) are fit parameters for thesymmetric Laplace expansion, (x′,y′) are intermediate results for thetouchscreen coordinates before taking account of any rotations andoffset, x₀ and y₀ are the touchscreen coordinates (x,y) immediatelyabove the (X,Y)=(0,0) display origin, and δθ′ is a rotation parameterthat is applied to touchscreen coordinates (x,y) rather than the displaycoordinates (X,Y).

$\begin{matrix}{x^{\prime} = {\overset{n \leq N}{\sum\limits_{n\mspace{11mu} {odd}}}{{\alpha_{X,n}^{\prime} \cdot {Re}}\left\{ \left( {X + {\; Y}} \right)^{n} \right\}}}} & {{Eq}.\mspace{14mu} 39} \\{y^{\prime} = {\overset{n \leq N}{\sum\limits_{n\mspace{11mu} {odd}}}{{\beta_{Y,n}^{\prime} \cdot {Im}}\left\{ \left( {X + {\; Y}} \right)^{n} \right\}}}} & {{Eq}.\mspace{14mu} 40}\end{matrix}$

Although typically only the display coordinates (X,Y) are Cartesiancoordinates that can be offset and rotated in this fashion, if thetouchscreen coordinates (x,y) are approximately Cartesian and the valuesof δθ′, x₀ and y₀ are small, Eq. 41 and 42 may be applied.

x=cos(δθ′)·x′−sin(δθ′)·y′+x ₀ ≈x′−δθ′·y′+x ₀  Eq. 41

y=sin(δθ′)·x′+cos(δθ′)·y′+y ₀ ≈y′+δθ′·x′+y ₀  Eq. 42

Provided that the calibration grid is both top/bottom and left/rightsymmetric, the parameters x₀ and y₀ can be computed as the average ofthe x and y coordinates of the calibration data. These offsets can beapplied to the calibration data,(x_(k),y_(k))→(x″_(k),y″_(k))≡(x_(k)−x₀, y_(k)−y₀) to produce centeredcalibration data. Furthermore, the calibration data(X″_(k),y″_(k))→(x′_(k),y′_(k)) may be made symmetric by definingx′_(k)=(x″_(k)+x″_(k′)−X″_(k″)−x″_(k′″))/4 andy′_(k)=(y″_(k)−y″_(k′)+y″_(k″)−y″_(k′″))/4 where indices k′, k″ and k′″are chosen so that (X_(k′),Y_(k′))=(+X_(k),−Y_(k)),(X_(k″),Y_(k″))=(−X_(k),+Y_(k)) and (X_(k′″),Y_(k″′))=(−X_(k),−Y_(k)).The symmetric Laplace-constrained fit parameters α′_(X,n), and β′_(Y,n)are determined by standard least squared fit to the symmetrizedcalibration data (x′_(k),y′_(k)) while the parameter δθ′ may beestimated by Eq. 43 where the sums are over the calibration grid indexk.

tan(δθ′)≈{[Σ(x″ _(k) ·y′ _(k) −x′ _(k) ·y″ _(k))]/[Σ(x″ _(k) ·x′ _(k)+y′ _(k) ,·y″ _(k))]}  Eq. 43

If the touchscreen coordinates (x,y) are nonlinear, a better estimatefor rotation 60′ may be obtained with Eq. 44 and 45 where D and D′represent the partial derivative with respect to 60 for the expansionsof x and y, respectively, in the quasi-symmetric Laplace-constrained fit(Eq. 37 and 38).

δθ′≈{[ΣD·(x′ _(k) −x″ _(k))]/Σ[D] ²}  Eq. 44

δθ′≈{[ΣD′·(y′ _(k) −y″ _(k))]/Σ[D′] ²}  Eq. 45

In other embodiments, the above equations can be re-expressed in anumber of mathematically equivalent ways. None of the equations hereinis limited to one or any particular coordinate system or mathematicnotation.

Returning to 204 of FIG. 3, in another embodiment the calibration module196 may accomplish an analytic conversion, which is a type of inversion.For example, the 3^(rd) order symmetric Laplace-constrained fit may beused to illustrate analytic inversion of the Laplace expansion as analternative to the virtual calibration grid method. The symmetricLaplace expansions x=α_(X,1)·X+α_(X,3) ·(X³−3XY²) andy=β_(Y,1)·Y+β_(Y,3)·(3X²Y−Y³) may be substituted back into thepolynomial expansion given in Eq. 3 and 4 for the horizontal displaycoordinate X as a function of touchscreen coordinates (x,y). Doing sowhile keeping only terms up to 3^(rd) order leads to Eq. 46.

$\begin{matrix}{X = {A_{0,0} + {A_{1,0} \cdot \left\{ {{\alpha_{X,1} \cdot X} + {\alpha_{X,3} \cdot \left( {X^{3} - {3{XY}^{2}}} \right)}} \right\}} + {A_{0,1} \cdot \left\{ {{\beta_{Y,1} \cdot Y} + {\beta_{Y,3} \cdot \left( {{3X^{2}Y} - Y^{3}} \right)}} \right\}} + {A_{2,0} \cdot \left( {\alpha_{X,1} \cdot X} \right\}^{2}} + {A_{1,1} \cdot \left\{ {\alpha_{X,1} \cdot X} \right\} \cdot \left\{ {\beta_{Y,1} \cdot Y} \right\}} + {A_{0,2} \cdot \left\{ {\beta_{Y,1} \cdot Y} \right\}^{2}} + {A_{3,0} \cdot \left\{ {\alpha_{X,1} \cdot X} \right\}^{3}} + {{A_{2,1} \cdot \left\{ {\alpha_{X,1} \cdot X} \right\}^{2}}\left\{ {\beta_{Y,1} \cdot Y} \right\}} + {{A_{1,2} \cdot \left\{ {\alpha_{X,1} \cdot X} \right\}}\left\{ {\beta_{Y,1} \cdot Y} \right\}^{2}} + {A_{0,3} \cdot \left\{ {\beta_{Y,1} \cdot Y} \right\}^{3}}}} & {{Eq}.\mspace{14mu} 46}\end{matrix}$

Collecting terms of equal powers of X and Y, Eq. 46 becomes Eq. 47.

$\begin{matrix}{0 = {A_{0,0} + {\left\{ {{A_{1,0} \cdot \alpha_{X,1}} - 1} \right\} \cdot X} + {\left\{ {A_{0,1} \cdot \beta_{Y,1}} \right\} \cdot Y} + {\left\{ {A_{2,0} \cdot \alpha_{X,1}^{2}} \right\} \cdot X^{2}} + {\left\{ {A_{1,1} \cdot \alpha_{X,1} \cdot \beta_{Y,1}} \right\} \cdot {XY}} + {\left\{ {A_{0,2} \cdot \beta_{Y,1}^{2}} \right\} \cdot Y^{2}} + {\left\{ {{A_{1,0} \cdot \alpha_{X,3}} + {A_{3,0} \cdot \alpha_{X,1}^{3}}} \right\} \cdot X^{3}} + {\left\{ {{{- 3} \cdot A_{1,0} \cdot \alpha_{X,3}} + {A_{2,1} \cdot \alpha_{X,1} \cdot \beta_{Y,1}^{2}}} \right\} \cdot {XY}^{2}} + {{\left\{ {{3{A_{0,1} \cdot \beta_{Y,3}}} + {A_{2,1} \cdot \alpha_{X,1}^{2} \cdot \beta_{Y,1}}} \right\} \cdot X^{2}}Y} + {\left\{ {{{- A_{0,1}} \cdot \beta_{Y,3}} + {A_{0,3} \cdot \beta_{Y,1}^{3}}} \right\} \cdot Y^{3}}}} & {{Eq}.\mspace{14mu} 47}\end{matrix}$

For Eq. 47 to be true for all possible values of X and Y, thecoefficient of each monomial term is to be zero, as shown in Eq. 48 thru57.

0=A_(0,0)  Eq. 48

0=A _(1,0)·α_(X,1)−1  Eq. 49

0=A _(0,1)·β_(Y,1)  Eq. 50

0=A _(2,0)·α_(x,1) ²  Eq. 51

0=A _(1,1)α_(X,1)·β_(Y,1)  Eq. 52

0=A _(0,2)·β_(Y,1) ²  Eq. 53

0=A _(1,0)·α_(X,3) +A _(3,0)·α_(X,1) ³  Eq. 54

0=−3·A _(1,0)·α_(X,3) +A _(1,2)·α_(X,1)·β_(Y,1) ²  Eq. 55

0=3A _(0,1)·β_(Y,3) +A _(2,1)·α_(X,1) ²·β_(Y,1)  Eq. 56

0=−A _(0,1)·β_(Y,3) +A _(0,3)·β_(Y,1) ³  Eq. 57

The ten equations Eq. 48 thru 57 have ten unknowns A_(0,0), A_(1,0),A_(0,1), A_(2,0), . . . A_(0,3) that can be solved as follows.

A _(1,0)=1/α_(X,1)  Eq. 58

A _(3,0)=−α_(X,3)/α_(X,1) ⁴  Eq. 59

A _(1,2)=3·α_(X,3)/(α_(X,1) ²·β_(Y,1) ²)  Eq. 60

A_(0,0)=A_(0,1)=A_(2,0)=A_(1,1)=A_(0,2)=A_(2,1)=A_(0,3)=0  Eq. 61

Similarly, back substituting into the polynomial expansion for thevertical display coordinate Y, Eq. 62 thru 65 may be obtained.

B _(0,1)=1/β_(Y,1)  Eq. 62

B _(0,3)=−β_(Y,3)/β_(Y,1)  Eq. 63

B _(2,1)=3−·β_(Y,3)/(β_(Y,1) ²·α_(X,1) ²)  Eq. 64

B_(0,0)=B_(1,0)=B_(2,0)=B_(1,1)=B_(0,2)=B_(1,2)=B_(3,0)=0  Eq. 65

The only non-zero coefficients are those that correspond to the(inverted) symmetry relations X(−x,y)=−X(x,y), X(x,−y)=+X(x,y),Y(−x,y)=+Y(x,y) and Y(x,−y)=−Y(x,y). Thus, once the Laplace expansioncoefficients α_(X,1), α_(X,3), β_(Y,1) and β_(Y), are determined at 202of FIG. 3, the coefficients A_(m,n) and B_(m,n) are easily computed withthe above analytic expressions at 204. The same principles may beapplied to generalize this analytic method to higher order symmetricLaplace-constrained fits as well as generalized Laplace-constrainedfits.

In the examples up to this point, the generalized Laplace-constrainedexpansions have been polynomial expansions. For computational purposes,polynomial expansions have the advantage of involving only addition andmultiplication without recourse to transcendental functions. It can beshown, however, that symmetric expansions Eq. 66 and 67 satisfyLaplace's equation.

x=(C _(X) /k _(X))·sin(k _(X)·(X−X ₀))·cos h(k _(X)·(Y−Y ₀))  Eq. 66

y=(C _(Y) /k _(Y))·cos h(k _(Y)·(X−X ₀))·sin(k _(Y)·(Y−Y ₀))  Eq. 67

where C_(X), k_(X), C_(Y) and k_(Y) are fit parameters.

Eq. 66 and 67 reproduce the 3^(rd) order terms of the symmetric Laplacepolynomial fit (Eq. 31 and 32) for the case of X₀=0 and Y₀=0 whereink_(X) and k_(Y) are sufficiently small that only terms up to 2^(nd)order is these parameters need be considered, C_(X)=α_(X,1) andC_(Y)=β_(Y,1) and C_(X)·k_(X) ²/6=−α_(X,3) and C_(Y)·k_(Y) ²/6=−β_(Y,3).In other embodiments, other terms corresponding to other productssatisfying Laplace's Equation of one trigonometric function and onehyperbolic function, such as sin h(k·X)·cos(k·Y), may be included.

Referring to the Laplace polynomial expansion in polar coordinates,terms of the form (α_(X,n)·R^(n)·cos(nφ) satisfy Laplace's equation notonly for integer values of n, but also any real value for n such as n=½.However, such expressions with non-integral n are no longer 2π periodic(that is, the expression has different values for 0° and 360°) and hencecannot be used to expand about an origin at the center of thetouchscreen 158. However, non-integer values of n are acceptable whenexpanding about a corner, for example. FIG. 10 illustrates a touchscreen348 having a touch point 358 in the touch sensitive area of thetouchscreen 348. The touchscreen 348 has corners 360, 362, 364 and 366.Radial distances R₁ 350, R₂ 352, R₃ 354, and R₄ 356 are the distances tothe touch point 358 (in display coordinates) from each of the fourcorners 360, 362, 364 and 366, respectively. Angles θ₁ 368, θ₂ 370, θ₃372, and θ₄ 374 are the angles formed between the horizontal edges ofthe touchscreen 348 and radial distances extending between each of thefour corners and the touch point 358. It is assumed that the touchdisplay system hardware is symmetric. In this case, Eq. 68 and 69provide an alternative parameterization for a Laplace-constrained fit.Such a parameterization involves only the six fit parameters C_(X),n_(X), θ_(X), C_(Y), n_(Y) and θ_(Y) and accounts for the somewhatsingular behavior at the corner regions of touchscreens such assymmetric picture-frame touchscreens.

x=C _(X) ·{+R ₁ ^(n) ^(x) ·cos(n _(X)·(θ₁−θ_(X)))−R ₂ ^(n) ^(x) ·cos(n_(X)·θ₂−θ_(X)))−R ₃ ^(n) ^(x) ·cos(n _(X)·(θ₃−θ_(X)))+R ₄ ^(n) ^(x)cos(n _(X)·(θ₄−θ_(X)))}  Eq. 68

y=C _(Y) ·{−R ₁ ^(n) ^(y) ·sin(n _(Y)·(θ₁−θ_(Y)))−R ₂ ^(n) ^(y) sin(n_(Y)·(θ₂-θ_(Y)))+R ₃ ^(n) ^(y) sin(n _(y)·(θ₃−θ_(Y)))+R ₄ ^(n) ^(y)·sin(n _(Y)·(θ₄−θ_(Y)))}  Eq. 69

Therefore, the Laplace-constrained fit may be based on distances fromthe touch point to each of the four corners of the touchscreen 348 aswell as the angle formed by the radial line with the horizontal edge ofthe touchscreen 348. If n_(X)=n_(Y)=1 and θ_(X)=θ_(Y)=0, then Eq. 68 and69 reduce to linear touchscreen coordinates x=α_(X,1)·X and y=β_(Y,1)·Ywith α_(X,1)=4C_(X) and β_(Y,1)=4C_(Y). For quasi-linear picture-frametouchscreens that deviate only slightly from linearity, n_(X) and n_(Y)deviate only slightly from one and θ_(X) and θ_(Y) will by only slightlydifferent than 0°. For more strongly non-linear picture-frametouchscreen designs, the fitted parameters n_(X) and n_(Y) will deviatefurther from one and θ_(X) and θ_(Y) may deviate further from zero.

Returning to 204 of FIG. 3, options for inverting Laplace-constrainedexpansions into expansions of display coordinates (X,Y) in terms oftouchscreen coordinates (x,y) include both the virtual grid method aswell as use of algebraic expressions or analytic inversion. Othermethods may be used to derive expansions of display coordinates (X,Y) interms of touchscreen coordinates (x,y) from expansions of touchscreencoordinates (x,y) in terms of display coordinates (X,Y). By using one ora combination of types of generalized Laplace-constrained fits, the fitis improved by reducing the number of fit parameters while requiringless calibration targets, and in some touchscreens 158, allowingcalibration grids that do not include interior calibration targets, andin some other touchscreens 158, reflecting the symmetry of the touchdisplay hardware.

It is to be understood that the above description is intended to beillustrative, and not restrictive. For example, the above-describedembodiments (and/or aspects thereof) may be used in combination witheach other. In addition, many modifications may be made to adapt aparticular situation or material to the teachings of the inventionwithout departing from its scope. While the dimensions and types ofmaterials described herein are intended to define the parameters of theinvention, they are by no means limiting and are exemplary embodiments.Many other embodiments will be apparent to those of skill in the artupon reviewing the above description. The scope of the invention should,therefore, be determined with reference to the appended claims, alongwith the full scope of equivalents to which such claims are entitled. Inthe appended claims, the terms “including” and “in which” are used asthe plain-English equivalents of the respective terms “comprising” and“wherein.” Moreover, in the following claims, the terms “first,”“second,” and “third,” etc. are used merely as labels, and are notintended to impose numerical requirements on their objects. Further, thelimitations of the following claims are not written inmeans-plus-function format and are not intended to be interpreted basedon 35 U.S.C. § 112, sixth paragraph, unless and until such claimlimitations expressly use the phrase “means for” followed by a statementof function void of further structure.

1. A method for calibrating a touch system, comprising: defining a setof calibration targets that have associated display coordinates(X_(i),Y_(i)) that are in a display coordinate system; acceptingtouchscreen coordinates (x_(i),y_(i)) that have noise, the touchscreencoordinates (x_(i),y_(i)) each being associated with one of thecalibration targets, the touchscreen coordinates being in a touchscreencoordinate system; and computing non-linear correction parameters basedon the touchscreen coordinates (x_(i),y_(i)) with respect to the displaycoordinates (X_(i),Y_(i)), the non-linear correction parameters defininga one-to-one correspondence between display coordinates (X,Y) andtouchscreen coordinates (x,y) that is non-linear, the computingproducing the one-to-one correspondence where an average magnitude of aLaplacian of at least one of x and y touchscreen coordinates withrespect to the display coordinates is smaller than an average magnitudeof a Laplacian of a one-to-one correspondence computed with aconventional general fit in the presence of the noise of the touchscreencoordinates (x_(i),y_(i)), the Laplacians of the x and y touchscreencoordinates being based on ∂²/∂X²+∂²x/∂Y² and ∂²y/∂X²+∂²y/∂Y²,respectively.
 2. The method of claim 1, wherein the average magnitude ofthe Laplacian of at least one of the x and y touchscreen coordinates isone of a group of zero and 10% of the average magnitude of a Laplacianof a one-to-one correspondence computed with a conventional general fitin the presence of the noise of the touchscreen coordinates(x_(i),y_(i)).
 3. The method of claim 1, wherein the noise is based onat least one of electronic noise and a misalignment between the displaycoordinates (X_(i),Y_(i)) of the set of calibration targets and theassociated touchscreen coordinates (x_(i),y_(i)).
 4. A computer readablemedium for calibrating a touch system, comprising: instructions todetect touch points on a touchscreen, the touch points each beingassociated with touchscreen coordinates in a touchscreen coordinatesystem; instructions to associate each of the touch points with knowncalibration targets, each of the calibration targets having displaycoordinates in a display coordinate system, the display coordinatesystem being associated with at least one of a display screen and anoperating system; and instructions to fit the display coordinates andthe touchscreen coordinates non-linearly with respect to each otherbased on a generalized Laplace-constrained fit, the fit being used toidentify correction parameters used to map a user generated run-timetouch point on the touchscreen to a display coordinate location on adisplay screen, the correction parameters representing non-linearcorrections.
 5. The computer readable medium of claim 4, furthercomprising instructions to generate virtual calibration data based on avirtual calibration grid that has more virtual calibration targets thanthe set of calibration targets, the virtual calibration data being usedto compute the correction parameters.
 6. The computer readable medium ofclaim 4, the instructions to fit further comprising generating apolynomial expansion based on the display coordinates and thetouchscreen coordinates.
 7. The computer readable medium of claim 4,wherein the calibration targets are located in one of a grid within thedisplay coordinate system, proximate to a perimeter of a touch areaassociated with the display coordinate system, and an outline within thetouch area associated with the display coordinate system.
 8. Thecomputer readable medium of claim 4, further comprising instructions togenerate a polynomial expansion to an Nth order based on the displaycoordinates and the touchscreen coordinates, the polynomial expansionhaving one polynomial term for every two orders.
 9. The computerreadable medium of claim 4, further comprising instructions to generatea polynomial expansion based on the display coordinates and thetouchscreen coordinates, the polynomial expansion further including atleast one term that violates Laplace's equation.
 10. The computerreadable medium of claim 9, wherein the at least one term that violatesLaplace's equation is based on a non-uniform gradient within thetouchscreen.
 11. The computer readable medium of claim 4, wherein thetouchscreen is symmetric in at least one of X and Y directions, themedium further comprising: instructions to generate a polynomialexpansion to Nth order based on the display coordinates and thetouchscreen coordinates; and instructions to include polynomial termswithin the polynomial expansion having only odd values of n and anoptional constant.
 12. The computer readable medium of claim 4, whereinthe touchscreen is symmetric in at least one of X and Y directions, themedium further comprising: instructions to generate a polynomialexpansion to Nth order based on the display coordinates and thetouchscreen coordinates; and instructions to modify the polynomialexpansion based at least one of a relative rotation and an offsetbetween the touchscreen and the display screen.
 13. The computerreadable medium of claim 4, the touchscreen further comprisinghorizontal edges along top and bottom sides, the medium furthercomprising: instructions to define radial distances R₁, R₂, R₃, and R₄that are distances to display coordinates (X,Y) from each of fourcorners of the touchscreen; instructions to define angles θ₁, θ₂, θ₃,and θ₄ that are formed between the horizontal edges and radial linesextending between each of the four corners and the display coordinates(X,Y); and instructions to perform a Laplace-constrained fit of touchcoordinates x and y in terms of the radial distances R₁, R₂, R₃, and R₄and the angles θ₁, θ₂, θ₃, and θ₄.
 14. The computer readable medium ofclaim 4, further comprising instructions to store the correctionparameters as one of monomial coefficients and constants for a look-uptable.
 15. The computer readable medium of claim 4, wherein thetouchscreen is one of a 5-wire resistive touchscreen, a 9-wire resistivetouchscreen and a capacitive touchscreen.
 16. A computer readable mediumfor calibrating a touch system, comprising: instructions to detectcalibration touch points on a touchscreen, the touch points each beingassociated with touchscreen coordinates in a touchscreen coordinatesystem; instructions to associate each of the touch points with knowncalibration targets, each of the calibration targets having displaycoordinates in a display coordinate system that is associated with adisplay screen, the calibration targets forming an outline in thedisplay coordinate system; and instructions to fit the displaycoordinates and the touchscreen coordinates non-linearly with respect toeach other, the fit being used to identify correction parameters used tomap touch points on the touchscreen to display coordinate locations onthe display screen.
 17. The computer readable medium of claim 16, theinstructions to fit further comprising: instructions to generategeneralized Laplace-constrained expansions to fit the touchscreencoordinates in terms of the display coordinates; and instructions toinvert the generalized Laplace-constrained expansions of the displaycoordinates in terms of the touchscreen coordinates based on one of avirtual calibration grid and an analytic conversion.
 18. The computerreadable medium of claim 16, wherein the instructions to fit are basedon terms that satisfy Laplace's equation.
 19. The computer readablemedium of claim 16, wherein the calibration targets comprise at leastsix calibration targets.
 20. The computer readable medium of claim 16,wherein each of the calibration targets forming the outline is separatedfrom a further closest neighboring calibration target by a distance thatis less than a radius of a largest inscribed circle centered in thedisplay coordinate system whose interior area is free of calibrationtargets.